7 Permanent Amazon SageMaker Jobs in the UK excluding London

using Python and the AWS Cloud Development Kit. You'll use a variety of services such as SNS, SQS and Lambda for event streams, Amazon Redshift, S3 and AWS Glue for data storage & reporting and Amazon SageMaker for our pioneering machine learning products. We are a growing … with our colleagues across ECS to help them use our services. Python and AWS Services such as S3, Kinesis, Lambda, Redshift, DynamoDB, Glue and SageMaker Infrastructure-as-Code tools and approaches (we use the AWS CDK with CloudFormation) Data processing frameworks such as pandas, Spark and PySpark Machine learning more »

engineering practices sch as CI/CD. Experience deploying/monitoring machine learning models and following best practices. The Ability to develop pipelines using SageMaker, MLFlow or similar frameworks. Strong experience with data programming frameworks such as Apache Spark. Understanding of common Data Science and Machine Learning models, libraries more »

and Engineering Teams to drive innovation and excellence About you Ability to Design and implement MLOps pipelines on AWS Experience with MLOps Frameworks, mainly SageMaker and MLFlow Strong programming experience in production environments (Python) Strong infrastructure knowledge (Terraform) Experience with DevOps tools (Docker, Kubernetes) Experience with integrating with data more »

for everybody. Your responsibilities: Work together with the AI labs, Data, Infrastructure, and Platform teams to design and deploy ML-based services using AWS Sagemaker and other cloud based solutions. Analyse current AWS account setup for data scientists & MLEs and improve it together with StSt MLE & DevOps experts. Understand more »

leading a data science team and managing complex projects. Expertise in machine learning, statistics, data management, and relevant technologies (e.g., Python, R, SQL, AWS SageMaker, Apache Airflow, Dbt, AWS Kinesis). Strong communication skills with the ability to explain complex data concepts to a non-technical audience. Knowledge of more »

different databases. Experience of architecting data solutions across hybrid (cloud, on-premise) data platforms. Knowledge of data science platforms such as Azure Machine Learning, Amazon SageMaker, Databricks, DataRobot, Snowflake etc., to enable the use of data and tie in with roadmap aspirations. Strong knowledge of data modelling, data more »

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